减少LIBSVM中的模型文件大小

我想减小模型文件的大小。我们可以通过减少模型文件权重中的位数来减少它吗。在我的模型文件中，类的数量大约为3800个，特征的数量大约为357000个。下面是模型文件的一些摘录。我可以减少这些权重中的位数吗

solver_type L2R_L2LOSS_SVC_DUAL
nr_class 3821
nr_feature 357021
bias -1.000000000000000
w
-0.6298615183549175 -0.6884816945277815 -0.9850473581929793
-0.2730180225739936 -0.4444522939544599 -0.3045368061994185 
-0.6752904784743610 -0.4936186126242763 -0.8167435931134331 
-0.8747648882598349 -0.4980187300672689 -0.8255372912521536 
-0.3329812532124196 -0.1751416471640286 -0.7447656595877303 
-0.4240569914873799 -0.9004909961812873 -0.9857813112641359 
-0.3674085365663847 -0.4819407419877990 -0.3645238468547681 
-0.5827397105860186 -0.7290781581209491 -0.8615229165775795 
-0.3975308017493017 -0.6522787326004871 -0.9846626520798610 
-0.5583216247458188 -0.9488816092738117 -0.6469158771901011 
-0.2306256734853684 -0.2940612946888093 -0.6895719661937446 
-0.3041407180695167 -0.5602587606930518 -0.4434458835686698 
-0.3960629365410545 -0.7512211790407204 -0.6082476608695304 
-1.336132842955273 -0.6057066303450040 -0.5726087731282288 
-0.4918814547677718 -0.7606578865363953 -0.2951659264868926 
-0.3881680788359501 -0.3109241231671961 -0.7078707491799914 
-0.3623625688446360 -0.4430137729068305 -0.9279271098475936 
-0.2290838088700753 -0.3870980678621480 -0.8000332693180561 
-0.7964744879675550 -0.4950551119251316 -0.5201500981458075 
-0.6654200978736288 -0.9037766341356712 -0.5921799507740539 
-0.4552915755388566 -0.8048467444625557 -0.08638961422716016 
-0.3175800991399296 -0.8889281355804046 -0.8889673432972257 
0.009443893188055608 -0.3033030733905986 -0.6063958370642328 
-0.7781676697747630 -0.9969339455729528 -0.7847641855193951 
-0.3709450948897945 -0.9293821956430142 -0.6711216076980766 
-0.6472048031763484 -0.2844660995208588 -0.4547657013618363 
-0.3093274839631762 -0.8264594986328345 -0.2693948669009715 
-0.5691246530468883 -0.5816949288414970 -0.7988407843132017 
-0.5846410991542126 -0.6102733673192773 -0.9474472897104326 
-0.4619018809588187 -0.6922626991585266 -0.8529509393486879 
-0.9341690394723746 -0.2048861760333368 -0.5763255438056814 
-0.4753823007333206 -0.9847858814169310 -0.6084670508904806 
-0.6097889096385636 -0.1558026578670219 -0.5407452525949980 
-0.8426597160875828 -0.5728578082647764 -0.6254655056167889 
-0.5002570985981800 -0.5660289375686121 -0.6966970933117435 
-0.3595184568720410 -0.8869769517170271 -0.8293060581021244 
-0.7660244640066636 -0.9191108227612158 -0.7495472111112249 
-0.3250789003708131 -0.8545862221106031 -0.9847863669982040 
-0.9862358540926807 -0.9843872487122278 -0.3764841688606632 
-0.6665806111063707 -0.6998869717621219 -0.8398491506346015 
-0.7498849663083538 -0.2584536929034274 -0.8798094698402976 
-0.8659064866640068 -0.8540212609217359 -0.4705628403387491 
-0.9848057457322186 -0.5870303872290659 -0.9105115844147157 
-0.6855534064105064 -0.7447256224770895 -0.9845164901161550 
-0.9267803381073205 -0.6874399094864110 -0.9868490844056681 
-0.9871049327408159 -0.9127271706215343 -0.8894132571749456 
-0.7481430771200624 -0.7661512147794380 -0.4619076734386954 
-0.3463253354355214 -0.7324122395130058 -0.7198934949704492 
-0.3869971300152642 -0.3580173602243875 -0.8144411145869335 
-0.4708508640578066 -0.7583061726079500 -0.6102585014526588 
-0.2323551831668570 -0.7124730357532248 -0.6407019387626708 
-0.8770555543363814 -0.7747723882503575 -0.8880529094965369 
-0.5221765657051773 -0.8927103129537772 -0.8873570244928761 
-0.6814118942525524 -0.4812414843861851 -0.07723442473878635 
-0.3004215736435181 -0.7901826925719376 -0.6000050603345796 
-0.9391488020802135 -0.6130019120301854 -0.6519260224181763 
-0.6312423953207323 -0.6236684911320279 -0.8319901021019791 
-0.9846585341126538 -0.8241847119432536 -0.9849733862258551 
0.03619613868867930 -0.9402473523400392 -0.4963043182116479 
-0.06988396609313940 -0.6160025364808686 -0.9485679374403244 
-0.9552678112333591 -0.2951058860501357 -0.9871232492575841 
-0.2801466899229405 -0.5623043303

---

我正试图解决一个类似的问题。删除数字会降低模型的准确性，因此最好避免使用。目前我有两个主要的选择，一是自己将模型文件转换成二进制格式，二是使用谷歌的协议缓冲区。当我有一个确定的解决方案时，我将返回更新。